
import unittest

from transformers import SPIECE_UNDERLINE, ReformerTokenizer, ReformerTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


lowercase    :   List[str]						=			get_tests_dir('fixtures/test_sentencepiece.model')




@require_sentencepiece
@require_tokenizers
class 					lowerCamelCase__				(							__lowercase	,		unittest.TestCase):




	'''simple docstring'''




	_A								=	ReformerTokenizer
	_A								=	ReformerTokenizerFast
	_A								=	True
	_A								=	False
	_A								=	True







	def   _lowerCamelCase							(   self						:Dict		)						->					Union[str, Any]:
								super().setUp()

								__UpperCamelCase      :  List[str]       =   ReformerTokenizer(a	,  keep_accents=a		)
								tokenizer.save_pretrained(self.tmpdirname		)







	def   _lowerCamelCase							(   self						:Union[str, Any]		)						->					Dict:
								__UpperCamelCase      :  int       =   "<s>"
								__UpperCamelCase      :  Dict       =   1

								self.assertEqual(self.get_tokenizer()._convert_token_to_id(a		)	,  a		)
								self.assertEqual(self.get_tokenizer()._convert_id_to_token(a		)	,  a		)







	def   _lowerCamelCase							(   self						:Dict		)						->					List[Any]:
								__UpperCamelCase      :  int       =   list(self.get_tokenizer().get_vocab().keys()		)

								self.assertEqual(vocab_keys[0]	,  "<unk>"		)
								self.assertEqual(vocab_keys[1]	,  "<s>"		)
								self.assertEqual(vocab_keys[-1]	,  "j"		)
								self.assertEqual(len(a		)	,  1_0_0_0		)







	def   _lowerCamelCase							(   self						:List[str]		)						->					str:
								self.assertEqual(self.get_tokenizer().vocab_size	,  1_0_0_0		)







	def   _lowerCamelCase							(   self						:List[str]		)						->					List[str]:
								if not self.test_rust_tokenizer:
															return

								__UpperCamelCase      :  Union[str, Any]       =   self.get_tokenizer()
								__UpperCamelCase      :  List[str]       =   self.get_rust_tokenizer()

								__UpperCamelCase      :  Union[str, Any]       =   "I was born in 92000, and this is falsé."

								__UpperCamelCase      :  List[str]       =   tokenizer.tokenize(a		)
								__UpperCamelCase      :  int       =   rust_tokenizer.tokenize(a		)
								self.assertListEqual(a	,  a		)

								__UpperCamelCase      :  List[str]       =   tokenizer.encode(a	,  add_special_tokens=a		)
								__UpperCamelCase      :  Tuple       =   rust_tokenizer.encode(a	,  add_special_tokens=a		)
								self.assertListEqual(a	,  a		)

								__UpperCamelCase      :  Union[str, Any]       =   self.get_rust_tokenizer()
								__UpperCamelCase      :  int       =   tokenizer.encode(a		)
								__UpperCamelCase      :  List[Any]       =   rust_tokenizer.encode(a		)
								self.assertListEqual(a	,  a		)







	def   _lowerCamelCase							(   self						:Tuple	,  a						:int=1_5		)						->					Any:
								for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
															with self.subTest(f'{tokenizer.__class__.__name__} ({pretrained_name})'		):
																						__UpperCamelCase      :  List[Any]       =   self.rust_tokenizer_class.from_pretrained(a	,  **a		)

																						# Simple input
																						__UpperCamelCase      :  Union[str, Any]       =   "This is a simple input"
																						__UpperCamelCase      :  Dict       =   ["This is a simple input 1", "This is a simple input 2"]
																						__UpperCamelCase      :  Tuple       =   ("This is a simple input", "This is a pair")
																						__UpperCamelCase      :  Optional[Any]       =   [
																						    ("This is a simple input 1", "This is a simple input 2"),
																						    ("This is a simple pair 1", "This is a simple pair 2"),
																						]

																						# Simple input tests
																						self.assertRaises(a	,  tokenizer_r.encode	,  a	,  max_length=a	,  padding="max_length"		)

																						# Simple input
																						self.assertRaises(a	,  tokenizer_r.encode_plus	,  a	,  max_length=a	,  padding="max_length"		)

																						# Simple input
																						self.assertRaises(
																						    a	,  tokenizer_r.batch_encode_plus	,  a	,  max_length=a	,  padding="max_length"	,  )

																						# Pair input
																						self.assertRaises(a	,  tokenizer_r.encode	,  a	,  max_length=a	,  padding="max_length"		)

																						# Pair input
																						self.assertRaises(a	,  tokenizer_r.encode_plus	,  a	,  max_length=a	,  padding="max_length"		)

																						# Pair input
																						self.assertRaises(
																						    a	,  tokenizer_r.batch_encode_plus	,  a	,  max_length=a	,  padding="max_length"	,  )







	def   _lowerCamelCase							(   self						:Union[str, Any]		)						->					str:
								pass







	def   _lowerCamelCase							(   self						:Union[str, Any]		)						->					Optional[Any]:
								__UpperCamelCase      :  List[Any]       =   ReformerTokenizer(a	,  keep_accents=a		)

								__UpperCamelCase      :  Tuple       =   tokenizer.tokenize("This is a test"		)
								self.assertListEqual(a	,  ["▁This", "▁is", "▁a", "▁t", "est"]		)

								self.assertListEqual(
								    tokenizer.convert_tokens_to_ids(a		)	,  [2_8_5, 4_6, 1_0, 1_7_0, 3_8_2]	,  )

								__UpperCamelCase      :  str       =   tokenizer.tokenize("I was born in 92000, and this is falsé."		)
								self.assertListEqual(
								    a	,  [
								        SPIECE_UNDERLINE + "I",
								        SPIECE_UNDERLINE + "was",
								        SPIECE_UNDERLINE + "b",
								        "or",
								        "n",
								        SPIECE_UNDERLINE + "in",
								        SPIECE_UNDERLINE + "",
								        "9",
								        "2",
								        "0",
								        "0",
								        "0",
								        ",",
								        SPIECE_UNDERLINE + "and",
								        SPIECE_UNDERLINE + "this",
								        SPIECE_UNDERLINE + "is",
								        SPIECE_UNDERLINE + "f",
								        "al",
								        "s",
								        "é",
								        ".",
								    ]	,  )
								__UpperCamelCase      :  Union[str, Any]       =   tokenizer.convert_tokens_to_ids(a		)
								self.assertListEqual(
								    a	,  [8, 2_1, 8_4, 5_5, 2_4, 1_9, 7, 0, 6_0_2, 3_4_7, 3_4_7, 3_4_7, 3, 1_2, 6_6, 4_6, 7_2, 8_0, 6, 0, 4]	,  )

								__UpperCamelCase      :  Union[str, Any]       =   tokenizer.convert_ids_to_tokens(a		)
								self.assertListEqual(
								    a	,  [
								        SPIECE_UNDERLINE + "I",
								        SPIECE_UNDERLINE + "was",
								        SPIECE_UNDERLINE + "b",
								        "or",
								        "n",
								        SPIECE_UNDERLINE + "in",
								        SPIECE_UNDERLINE + "",
								        "<unk>",
								        "2",
								        "0",
								        "0",
								        "0",
								        ",",
								        SPIECE_UNDERLINE + "and",
								        SPIECE_UNDERLINE + "this",
								        SPIECE_UNDERLINE + "is",
								        SPIECE_UNDERLINE + "f",
								        "al",
								        "s",
								        "<unk>",
								        ".",
								    ]	,  )







	@cached_property
	def   _lowerCamelCase							(   self						:Any		)						->					List[str]:
								return ReformerTokenizer.from_pretrained("google/reformer-crime-and-punishment"		)







	@slow
	def   _lowerCamelCase							(   self						:List[Any]		)						->					Dict:
								__UpperCamelCase      :  int       =   "Hello World!"
								__UpperCamelCase      :  Union[str, Any]       =   [1_2_6, 3_2, 2_6_2, 1_5_2, 3_8, 7_2, 2_8_7]

								self.assertListEqual(a	,  self.big_tokenizer.encode(a		)		)







	@slow
	def   _lowerCamelCase							(   self						:Optional[Any]		)						->					List[str]:
								__UpperCamelCase      :  Dict       =   (
								    "This is a very long text with a lot of weird characters, such as: . , ~ ? ( ) \" [ ] ! : - . Also we will"
								    " add words that should not exsist and be tokenized to <unk>, such as saoneuhaoesuth"
								)
								__UpperCamelCase      :  List[Any]       =   [
								    1_0_8,
								    2_6_5,
								    2_4,
								    1_1_1,
								    4,
								    2_5_8,
								    1_5_6,
								    3_5,
								    2_8,
								    2_7_5,
								    3,
								    2_5_9,
								    2_9_7,
								    2_6_0,
								    8_4,
								    4,
								    3_5,
								    1_1_0,
								    4_4,
								    8,
								    2_5_9,
								    9_1,
								    2_6_8,
								    2_1,
								    1_1,
								    2_0_9,
								    2_7_4,
								    1_0_9,
								    2_6_6,
								    2_7_7,
								    1_1_7,
								    8_6,
								    9_3,
								    3_1_5,
								    2_5_8,
								    2_7_8,
								    2_5_8,
								    2_7_7,
								    2_5_8,
								    0,
								    2_5_8,
								    2_8_8,
								    2_5_8,
								    3_1_9,
								    2_5_8,
								    0,
								    2_5_8,
								    0,
								    2_5_8,
								    0,
								    2_5_8,
								    0,
								    2_5_8,
								    2_8_7,
								    2_5_8,
								    3_1_5,
								    2_5_8,
								    2_8_9,
								    2_5_8,
								    2_7_8,
								    9_9,
								    2_6_9,
								    2_6_6,
								    2_6_2,
								    8,
								    2_5_9,
								    2_4_1,
								    4,
								    2_1_7,
								    2_3_0,
								    2_6_8,
								    2_6_6,
								    5_5,
								    1_6_8,
								    1_0_6,
								    7_5,
								    1_9_3,
								    2_6_6,
								    2_2_3,
								    2_7,
								    4_9,
								    2_6,
								    2_8_2,
								    2_5,
								    2_6_4,
								    2_9_9,
								    1_9,
								    2_6,
								    0,
								    2_5_8,
								    2_7_7,
								    1_1_7,
								    8_6,
								    9_3,
								    1_7_6,
								    1_8_3,
								    2_7_0,
								    1_1,
								    2_6_2,
								    4_2,
								    6_1,
								    2_6_5,
								]

								self.assertListEqual(a	,  self.big_tokenizer.encode(a		)		)







	@require_torch
	@slow
	def   _lowerCamelCase							(   self						:List[Any]		)						->					List[Any]:
								import torch

								from transformers import ReformerConfig, ReformerModel

								# Build sequence
								__UpperCamelCase      :  Tuple       =   list(self.big_tokenizer.get_vocab().keys()		)[:1_0]
								__UpperCamelCase      :  Union[str, Any]       =   " ".join(a		)
								__UpperCamelCase      :  Tuple       =   self.big_tokenizer.encode_plus(a	,  return_tensors="pt"		)
								__UpperCamelCase      :  Optional[int]       =   self.big_tokenizer.batch_encode_plus([sequence, sequence]	,  return_tensors="pt"		)

								__UpperCamelCase      :  Optional[Any]       =   ReformerConfig()
								# The input gets padded during training so adjust the axial position encodings from the pretrained model value of (512, 1024)
								__UpperCamelCase      :  Tuple       =   encoded_sequence["input_ids"].shape
								__UpperCamelCase      :  int       =   ReformerModel(a		)

								# Reformer has config.vocab_size == tokenizer.vocab_size == len(tokenizer) - 1 = 320; len(tokenizer) is 321 (including a pad token with id 320)
								assert model.get_input_embeddings().weight.shape[0] >= self.big_tokenizer.vocab_size

								with torch.no_grad():
															model(**a		)
															model(**a		)







	@slow
	def   _lowerCamelCase							(   self						:Optional[Any]		)						->					Any:
								# fmt: off
								__UpperCamelCase      :  Any       =   {"input_ids": [[1_0_8, 2_6_5, 2_4, 1_1_1, 4, 2_5_8, 1_5_6, 7, 5_1, 2_7_9, 5_8, 7, 7_6, 2_5, 6_9, 2_7_8], [1_4_0, 2_4_3, 2_6_4, 1_3_4, 1_7, 2_6_7, 7_7, 2_6_3, 2_2, 2_6_2, 2_9_7, 2_5_8, 3_0_4, 1_7_7, 2_7_9, 2_6_6, 1_4, 8_9, 1_3, 3_5, 2_6_1, 2_9_9, 2_7_2, 1_3_7, 2_7_5, 2_7_8]], "attention_mask": [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]}  # noqa: E501
								# fmt: on

								# This tokenizer does not know some characters like ")".
								# That is the reason why we use very simple texts here.
								# Also see https://github.com/huggingface/transformers/pull/11737#issuecomment-850769064
								__UpperCamelCase      :  List[str]       =   [
								    "This is a very simple sentence.",
								    "The quick brown fox jumps over the lazy dog.",
								]

								self.tokenizer_integration_test_util(
								    expected_encoding=a	,  model_name="google/reformer-crime-and-punishment"	,  revision="0e6c3decb8211d49bf881013425dc8b0448b3f5a"	,  padding=a	,  sequences=a	,  )

import unittest

from transformers.testing_utils import require_bsa
from transformers.utils import is_bsa_available

from ...test_feature_extraction_common import FeatureExtractionSavingTestMixin


if is_bsa_available():
		from transformers import MarkupLMFeatureExtractor




class 					lowerCamelCase__				(							unittest.TestCase):




	'''simple docstring'''




	def __init__(   self						:Optional[int]	,  a						:List[str]		)						->					Union[str, Any]:
								__UpperCamelCase      :  Dict       =   parent







	def   _lowerCamelCase							(   self						:Dict		)						->					int:
								return {}




def       _SCREAMING_SNAKE_CASE   (						)   ->       Optional[Any]:






							'''simple docstring'''





							__UpperCamelCase      :  Union[str, Any]       =   "<HTML>\n\n    <HEAD>\n    <TITLE>sample document</TITLE>\n    </HEAD>\n\n    <BODY BGCOLOR=\"FFFFFF\">\n    <HR>\n    <a href=\"http://google.com\">Goog</a>\n    <H1>This is one header</H1>\n    <H2>This is a another Header</H2>\n    <P>Travel from\n        <P>\n        <B>SFO to JFK</B>\n        <BR>\n        <B><I>on May 2, 2015 at 2:00 pm. For details go to confirm.com </I></B>\n        <HR>\n        <div style=\"color:#0000FF\">\n            <h3>Traveler <b> name </b> is\n            <p> John Doe </p>\n        </div>"

							__UpperCamelCase      :  Optional[int]       =   "\n    <!DOCTYPE html>\n    <html>\n    <body>\n\n    <h1>My First Heading</h1>\n    <p>My first paragraph.</p>\n\n    </body>\n    </html>\n    "

							return [html_string_a, html_string_a]




@require_bsa
class 					lowerCamelCase__				(							__lowercase	,		unittest.TestCase):




	'''simple docstring'''




	_A								=	MarkupLMFeatureExtractor if is_bsa_available() else None







	def   _lowerCamelCase							(   self						:List[str]		)						->					str:
								__UpperCamelCase      :  List[str]       =   MarkupLMFeatureExtractionTester(self		)







	@property
	def   _lowerCamelCase							(   self						:List[Any]		)						->					List[str]:
								return self.feature_extract_tester.prepare_feat_extract_dict()







	def   _lowerCamelCase							(   self						:Dict		)						->					Dict:
								# Initialize feature_extractor
								__UpperCamelCase      :  Tuple       =   self.feature_extraction_class()

								# Test not batched input
								__UpperCamelCase      :  Union[str, Any]       =   get_html_strings()[0]
								__UpperCamelCase      :  Any       =   feature_extractor(a		)

								# fmt: off
								__UpperCamelCase      :  Union[str, Any]       =   [["sample document", "Goog", "This is one header", "This is a another Header", "Travel from", "SFO to JFK", "on May 2, 2015 at 2:00 pm. For details go to confirm.com", "Traveler", "name", "is", "John Doe"]]
								__UpperCamelCase      :  Tuple       =   [["/html/head/title", "/html/body/a", "/html/body/h1", "/html/body/h2", "/html/body/p", "/html/body/p/p/b[1]", "/html/body/p/p/b[2]/i", "/html/body/p/p/div/h3", "/html/body/p/p/div/h3/b", "/html/body/p/p/div/h3", "/html/body/p/p/div/h3/p"]]
								# fmt: on

								self.assertEqual(encoding.nodes	,  a		)
								self.assertEqual(encoding.xpaths	,  a		)

								# Test batched
								__UpperCamelCase      :  str       =   get_html_strings()
								__UpperCamelCase      :  List[Any]       =   feature_extractor(a		)

								# fmt: off
								__UpperCamelCase      :  Optional[int]       =   expected_nodes + [["My First Heading", "My first paragraph."]]
								__UpperCamelCase      :  Tuple       =   expected_xpaths + [["/html/body/h1", "/html/body/p"]]

								self.assertEqual(len(encoding.nodes		)	,  2		)
								self.assertEqual(len(encoding.xpaths		)	,  2		)

								self.assertEqual(encoding.nodes	,  a		)
								self.assertEqual(encoding.xpaths	,  a		)